Answer / Syed Husain Akbar

Supervised Learning and Unsupervised Learning are two main types of Machine Learning methods. In Supervised Learning, the algorithm learns from labeled data, meaning each example in the training set has a predefined output or label.nThe goal is for the algorithm to learn a mapping function between inputs (features) and outputs (labels). Examples include classification (predicting categorical labels such as spam vs. not spam) and regression (predicting continuous values like house prices).nUnsupervised Learning, on the other hand, involves learning from unlabeled data, meaning there are no predefined output or label values.nThe goal is for the algorithm to discover hidden patterns or structure in the data without explicit guidance. Examples include clustering (grouping similar examples) and dimensionality reduction (reducing the number of features while preserving as much information as possible).

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